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Cite as

Ferreira, Ana M. G. (2024): Upward mantle flow from novel seismic observations (UPFLOW). GFZ Data Services. Dataset/Seismic Network. doi:10.14470/3W055238.

Identifier

10.14470/3W055238

DataCite metadata

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Terms/rights

Creative Commons Attribution 4.0 International Request access

Creator(s)

Ferreira, Ana M. G. ^a
a University College London, Great Britain

Description

• (Abstract) The goal of the UPFLOW project is to develop new high-resolution seismic imaging approaches along with new data collection, and to use them to constrain upward flow in unprecedented detail. We conducted a large off-shore experiment in the Azores-Madeira-Canary Islands region, which is a unique natural laboratory with multiple upwellings that are poorly understood in general. UPFLOW deployed and recovered 49 ocean bottom seismometers (OBSs) in a ~1,000×2,000 km2 area in the Azores-Madeira-Canary Islands region starting in July 2021 for ~13 months, with an average spacing of ~150-200 km. The seismic deployment and recovery involved institutions from five different countries: Portugal (IPMA, IDL, Univ. of Lisbon, ISEL), Ireland (DIAS), UK (UCL), Spain (ROA) and Germany (Potsdam University, GFZ, Geomar, AWI). 32 OBSs were rented from the DEPAS international pool of instruments maintained by the Alfred Wegener Institute (Bremerhaven), Germany, while other institutions borrowed additional instruments (7 from DIAS, 4 from IDL, 3 from ROA, 4 from GEOMAR). Most of the instruments have three-component wideband seismic sensors, but three different designs of OBS frames were used. Waveform data is available from the GEOFON data centre, under network code 8J, embargoed data may be accessible upon request. We want to acknowledge the exceptional support of the whole team of able seaman, steward, cooks, engineers, mechanicians, electricians and motorman assistants of the vessel RRV Mário Ruivo. With special Thanks to José Ângelo Gomes (Captain), Luís Ramos (Superintendent), Mafalda Carapuço Vessel’s manager (IPMA), Henrique Ferreira Land logistics (IPMA), Celine Ahmed and Jen Amery (Administrative support at UCL)

Title

Upward mantle flow from novel seismic observations (UPFLOW)

Publisher

GFZ Data Services

Publication Year

2024

Resource Type

Dataset / Seismic Network

Dates

1. Collected 2021-01-01
2. Accepted 2022-03-01
3. Created 2024-04-26
4. Available 2028-05-01

Place(s)

1. Azores-Madeira-Canary Islands

Contributor(s)

• Hosting institution: Deutsches GeoForschungsZentrum GFZ
• Data manager: GEOFON Data Centre
• Sponsors: DIAS; IDL; ROA; GEOMAR
• Project leader: University College London, Great Britain
• Other contributors: Miguel Miranda; Sameneh Baranbooei; Roberto Cabieces Diaz; Carlos Corela; José Luis Duarte; Henrique Ferreira; Wolfram H. Geissler; Katrina Harris; Stephen Hicks; Kasra Hosseini; Kuan-Yu Ke; Frank Krueger; Dietrich Lange; Afonso Loureiro; Peter Makus; Augustin Marignier; Marta Neres; Luis Ramos; Theresa Rein; Alex Saoulis; David Schlaphorst; Frederik Tilmann; Maria Tsekhmistrenko; José Ângelo Gomes (Captain); Luís Ramos (Superintendent); Mafalda Carapuço Vessel’s manager (IPMA); Henrique Ferreira Land logistics (IPMA); Celine Ahmed and Jen Amery (Administrative support at UCL)

Subjects

• SeisData terms: Amphibious DEPAS Pool Geophysics Mantle plume MiniSEED Natural OBS Passive seismic Pressure Regional network Temporary Three-component Velocity
• GCMD keywords: Marine geophysics Earthquakes Seismometers
• Other terms: GEOMAR; IDL; ROA; iMarl-DIAS

Funding Reference(s)

1. European Research Council (101001601)

Language

en

Sizes

1. 2700GB

Reference(s)

1. European Commission (2020). Upward mantle flow from novel seismic observations. Project Description, CORDIS EU research results. doi:10.3030/101001601 DOI
2. Schmidt-Aursch, Mechita; Haberland, Christian (2017). DEPAS (Deutscher Geräte-Pool für amphibische Seismologie): German Instrument Pool for Amphibian Seismology. Journal of large-scale research facilities JLSRF. doi:10.17815/jlsrf-3-165 DOI

FDSN network code

8J

Network dates

2021–2023

Data time range

2021–2023

Station Count

49

Seismic metadata

fdsnws-station FDSN StationXML SC3 XML

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